The present embodiments relate to natural language processing and electronic image processing. More specifically, the embodiment relate to cognitive computing and deep learning to integrate product search and motivation in an electronic environment.
In the field of artificially intelligent computer systems, natural language systems (such as the IBM Watson™ artificially intelligent computer system or and other natural language question answering systems) process natural language based on knowledge acquired by the system. To process natural language, the system may be trained with data derived from a data source or corpus of knowledge.
Machine learning (ML), which is a subset of Artificial intelligence (AI), utilizes algorithms to learn from data and create foresights based on this data. AI refers to the intelligence when machines, based on information, are able to make decisions, which maximizes the chance of success in a given topic. More specifically, AI is able to learn from a data set to solve problems and provide relevant recommendations. AI is a subset of cognitive computing, which refers to systems that learn at scale, reason with purpose, and naturally interact with humans. Cognitive computing is a mixture of computer science and cognitive science. Cognitive computing utilizes self-teaching algorithms that use data minimum, visual recognition, and natural language processing to solve problems and optimize human processes.